Data Cleaning publication categorizer

This paper presents a set of algorithms for distinguishing personal names with multiple real referents in text, based on little or no supervision. The approach utilizes an unsupervised clustering technique over a rich feature space of biographic facts, which are automatically extracted via a language-independent bootstrapping process. The induced clustering of named entities are then partitioned and linked to their real referents via the automatically extracted biographic data.